Overview

Dataset statistics

Number of variables16
Number of observations11065619
Missing cells0
Missing cells (%)0.0%
Duplicate rows1065683
Duplicate rows (%)9.6%
Total size in memory1.4 GiB
Average record size in memory136.0 B

Variable types

Numeric16

Alerts

Dataset has 1065683 (9.6%) duplicate rowsDuplicates
voltage is highly overall correlated with current and 7 other fieldsHigh correlation
current is highly overall correlated with voltage and 3 other fieldsHigh correlation
power is highly overall correlated with voltage and 8 other fieldsHigh correlation
energy is highly overall correlated with workstation_cpu_power and 3 other fieldsHigh correlation
power_factor is highly overall correlated with workstation_cpu_power and 2 other fieldsHigh correlation
workstation_cpu is highly overall correlated with voltage and 8 other fieldsHigh correlation
workstation_cpu_power is highly overall correlated with voltage and 9 other fieldsHigh correlation
workstation_cpu_temperature is highly overall correlated with voltage and 9 other fieldsHigh correlation
workstation_gpu_power is highly overall correlated with voltage and 8 other fieldsHigh correlation
workstation_gpu_temperature is highly overall correlated with power and 7 other fieldsHigh correlation
workstation_ram is highly overall correlated with voltage and 8 other fieldsHigh correlation
workstation_ram_power is highly overall correlated with voltage and 8 other fieldsHigh correlation
esp32_temperature has 3061149 (27.7%) zerosZeros
workstation_cpu has 6764177 (61.1%) zerosZeros
workstation_cpu_power has 7758484 (70.1%) zerosZeros
workstation_cpu_temperature has 7758486 (70.1%) zerosZeros
workstation_gpu has 10793423 (97.5%) zerosZeros
workstation_gpu_power has 7758486 (70.1%) zerosZeros
workstation_gpu_temperature has 8065750 (72.9%) zerosZeros
workstation_ram has 6675954 (60.3%) zerosZeros
workstation_ram_power has 7758486 (70.1%) zerosZeros

Reproduction

Analysis started2023-07-25 02:23:16.755294
Analysis finished2023-07-25 02:30:01.342860
Duration6 minutes and 44.59 seconds
Software versionydata-profiling vv4.3.2
Download configurationconfig.json

Variables

weekday
Real number (ℝ)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1034053
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size168.8 MiB
2023-07-25T04:30:01.376512image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.9884778
Coefficient of variation (CV)0.4845921
Kurtosis-1.2117191
Mean4.1034053
Median Absolute Deviation (MAD)2
Skewness-0.1130189
Sum45406720
Variance3.9540441
MonotonicityNot monotonic
2023-07-25T04:30:01.412210image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
4 1793610
16.2%
5 1790363
16.2%
6 1659657
15.0%
7 1605471
14.5%
1 1540765
13.9%
2 1483798
13.4%
3 1191955
10.8%
ValueCountFrequency (%)
1 1540765
13.9%
2 1483798
13.4%
3 1191955
10.8%
4 1793610
16.2%
5 1790363
16.2%
6 1659657
15.0%
7 1605471
14.5%
ValueCountFrequency (%)
7 1605471
14.5%
6 1659657
15.0%
5 1790363
16.2%
4 1793610
16.2%
3 1191955
10.8%
2 1483798
13.4%
1 1540765
13.9%

voltage
Real number (ℝ)

HIGH CORRELATION 

Distinct43
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean120.02132
Minimum116.1
Maximum120.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size168.8 MiB
2023-07-25T04:30:01.461105image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum116.1
5-th percentile119.6
Q1120
median120.1
Q3120.1
95-th percentile120.5
Maximum120.6
Range4.5
Interquartile range (IQR)0.1

Descriptive statistics

Standard deviation0.30542714
Coefficient of variation (CV)0.0025447739
Kurtosis16.340703
Mean120.02132
Median Absolute Deviation (MAD)0.1
Skewness-3.4240325
Sum1.3281102 × 109
Variance0.093285736
MonotonicityNot monotonic
2023-07-25T04:30:01.507790image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
120 3497786
31.6%
120.1 3420896
30.9%
120.2 1675175
15.1%
119.9 976188
 
8.8%
120.5 579419
 
5.2%
119.6 353741
 
3.2%
119.8 96220
 
0.9%
118.3 86795
 
0.8%
118.9 85433
 
0.8%
120.4 66245
 
0.6%
Other values (33) 227721
 
2.1%
ValueCountFrequency (%)
116.1 3
 
< 0.1%
116.2 3
 
< 0.1%
116.5 1
 
< 0.1%
116.7 1
 
< 0.1%
116.8 4
 
< 0.1%
116.9 5
< 0.1%
117 10
< 0.1%
117.1 4
 
< 0.1%
117.2 7
< 0.1%
117.3 8
< 0.1%
ValueCountFrequency (%)
120.6 788
 
< 0.1%
120.5 579419
 
5.2%
120.4 66245
 
0.6%
120.3 15
 
< 0.1%
120.2 1675175
15.1%
120.1 3420896
30.9%
120 3497786
31.6%
119.9 976188
 
8.8%
119.8 96220
 
0.9%
119.7 12005
 
0.1%

current
Real number (ℝ)

HIGH CORRELATION 

Distinct1092
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.82034394
Minimum0.02
Maximum2.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size168.8 MiB
2023-07-25T04:30:01.554380image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.02
5-th percentile0.13
Q10.68
median0.92
Q30.94
95-th percentile1.057
Maximum2.1
Range2.08
Interquartile range (IQR)0.26

Descriptive statistics

Standard deviation0.23061584
Coefficient of variation (CV)0.28112091
Kurtosis2.1688513
Mean0.82034394
Median Absolute Deviation (MAD)0.11
Skewness-1.421553
Sum9077613.5
Variance0.053183665
MonotonicityNot monotonic
2023-07-25T04:30:01.601222image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.92 1561932
14.1%
0.93 1446578
 
13.1%
0.62 1101668
 
10.0%
0.94 813172
 
7.3%
0.13 640347
 
5.8%
0.61 639726
 
5.8%
0.69 411616
 
3.7%
1.03 292740
 
2.6%
1.04 275381
 
2.5%
1.02 257373
 
2.3%
Other values (1082) 3625086
32.8%
ValueCountFrequency (%)
0.02 5995
 
0.1%
0.09 85
 
< 0.1%
0.1 2
 
< 0.1%
0.11 4
 
< 0.1%
0.12 10
 
< 0.1%
0.13 640347
5.8%
0.16 3
 
< 0.1%
0.19 2
 
< 0.1%
0.21 1
 
< 0.1%
0.22 2
 
< 0.1%
ValueCountFrequency (%)
2.1 4
< 0.1%
2.09 3
< 0.1%
2.08 1
 
< 0.1%
1.98 1
 
< 0.1%
1.976 1
 
< 0.1%
1.957 1
 
< 0.1%
1.944 1
 
< 0.1%
1.94 3
< 0.1%
1.93 5
< 0.1%
1.928 2
 
< 0.1%

power
Real number (ℝ)

HIGH CORRELATION 

Distinct1368
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean87.191899
Minimum0
Maximum245.6
Zeros6074
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size168.8 MiB
2023-07-25T04:30:01.648511image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.9
Q176.6
median95
Q398.8
95-th percentile113.9
Maximum245.6
Range245.6
Interquartile range (IQR)22.2

Descriptive statistics

Standard deviation25.869717
Coefficient of variation (CV)0.29669862
Kurtosis3.4431944
Mean87.191899
Median Absolute Deviation (MAD)13.3
Skewness-1.6896999
Sum9.6483234 × 108
Variance669.24224
MonotonicityNot monotonic
2023-07-25T04:30:01.699019image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.9 402450
 
3.6%
94.9 355265
 
3.2%
94.8 351782
 
3.2%
95 285556
 
2.6%
94.7 259319
 
2.3%
4.8 237737
 
2.1%
66.1 218663
 
2.0%
95.1 216869
 
2.0%
66.2 187526
 
1.7%
66 179935
 
1.6%
Other values (1358) 8370517
75.6%
ValueCountFrequency (%)
0 6074
0.1%
0.4 5
 
< 0.1%
0.8 1
 
< 0.1%
1.1 1
 
< 0.1%
1.2 1
 
< 0.1%
2.2 1
 
< 0.1%
2.5 2
 
< 0.1%
2.9 1
 
< 0.1%
3.8 1
 
< 0.1%
4.1 2
 
< 0.1%
ValueCountFrequency (%)
245.6 1
< 0.1%
245.1 1
< 0.1%
245 2
< 0.1%
244.6 1
< 0.1%
244.5 1
< 0.1%
244.2 1
< 0.1%
243.3 1
< 0.1%
226.6 1
< 0.1%
223.3 1
< 0.1%
221.1 1
< 0.1%

frequency
Real number (ℝ)

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.96468
Minimum59.3
Maximum60.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size168.8 MiB
2023-07-25T04:30:01.739990image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum59.3
5-th percentile59.9
Q159.9
median60
Q360
95-th percentile60
Maximum60.3
Range1
Interquartile range (IQR)0.1

Descriptive statistics

Standard deviation0.049704949
Coefficient of variation (CV)0.00082890377
Kurtosis-0.7624344
Mean59.96468
Median Absolute Deviation (MAD)0
Skewness-0.82633497
Sum6.635463 × 108
Variance0.002470582
MonotonicityNot monotonic
2023-07-25T04:30:01.776832image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
60 7250525
65.5%
59.9 3712301
33.5%
59.8 99556
 
0.9%
60.1 3170
 
< 0.1%
59.7 46
 
< 0.1%
60.2 18
 
< 0.1%
60.3 1
 
< 0.1%
59.3 1
 
< 0.1%
59.4 1
 
< 0.1%
ValueCountFrequency (%)
59.3 1
 
< 0.1%
59.4 1
 
< 0.1%
59.7 46
 
< 0.1%
59.8 99556
 
0.9%
59.9 3712301
33.5%
60 7250525
65.5%
60.1 3170
 
< 0.1%
60.2 18
 
< 0.1%
60.3 1
 
< 0.1%
ValueCountFrequency (%)
60.3 1
 
< 0.1%
60.2 18
 
< 0.1%
60.1 3170
 
< 0.1%
60 7250525
65.5%
59.9 3712301
33.5%
59.8 99556
 
0.9%
59.7 46
 
< 0.1%
59.4 1
 
< 0.1%
59.3 1
 
< 0.1%

energy
Real number (ℝ)

HIGH CORRELATION 

Distinct45882
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean122.39697
Minimum0
Maximum442.626
Zeros82
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size168.8 MiB
2023-07-25T04:30:01.820735image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6.46
Q138.31
median119.99
Q3173.52
95-th percentile276.77
Maximum442.626
Range442.626
Interquartile range (IQR)135.21

Descriptive statistics

Standard deviation98.100056
Coefficient of variation (CV)0.80149087
Kurtosis1.4894105
Mean122.39697
Median Absolute Deviation (MAD)72.76
Skewness1.1365584
Sum1.3543983 × 109
Variance9623.6209
MonotonicityNot monotonic
2023-07-25T04:30:01.868045image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
137.1 7730
 
0.1%
137.43 7723
 
0.1%
136.99 7720
 
0.1%
137.24 7719
 
0.1%
137.29 7719
 
0.1%
136.93 7718
 
0.1%
137.07 7717
 
0.1%
136.6 7716
 
0.1%
136.85 7715
 
0.1%
136.49 7714
 
0.1%
Other values (45872) 10988428
99.3%
ValueCountFrequency (%)
0 82
 
< 0.1%
0.02 570
< 0.1%
0.03 687
< 0.1%
0.04 678
< 0.1%
0.05 760
< 0.1%
0.06 704
< 0.1%
0.07 638
< 0.1%
0.08 651
< 0.1%
0.09 759
< 0.1%
0.1 686
< 0.1%
ValueCountFrequency (%)
442.626 13
< 0.1%
442.625 31
< 0.1%
442.624 25
< 0.1%
442.623 31
< 0.1%
442.622 26
< 0.1%
442.621 29
< 0.1%
442.62 31
< 0.1%
442.619 25
< 0.1%
442.618 30
< 0.1%
442.617 25
< 0.1%

power_factor
Real number (ℝ)

HIGH CORRELATION 

Distinct57
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.86025335
Minimum0
Maximum1
Zeros6074
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size168.8 MiB
2023-07-25T04:30:01.918208image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.32
Q10.86
median0.89
Q30.9
95-th percentile0.97
Maximum1
Range1
Interquartile range (IQR)0.04

Descriptive statistics

Standard deviation0.13945405
Coefficient of variation (CV)0.16210811
Kurtosis10.851852
Mean0.86025335
Median Absolute Deviation (MAD)0.03
Skewness-3.4260506
Sum9519235.8
Variance0.019447431
MonotonicityNot monotonic
2023-07-25T04:30:01.967705image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.86 3253719
29.4%
0.9 2399702
21.7%
0.89 1296058
 
11.7%
0.94 678932
 
6.1%
0.32 609354
 
5.5%
0.97 538312
 
4.9%
0.85 391609
 
3.5%
0.95 361836
 
3.3%
0.87 328359
 
3.0%
0.91 299376
 
2.7%
Other values (47) 908362
 
8.2%
ValueCountFrequency (%)
0 6074
0.1%
0.03 4
 
< 0.1%
0.04 1
 
< 0.1%
0.07 1
 
< 0.1%
0.09 1
 
< 0.1%
0.1 1
 
< 0.1%
0.17 1
 
< 0.1%
0.19 2
 
< 0.1%
0.21 1
 
< 0.1%
0.27 1
 
< 0.1%
ValueCountFrequency (%)
1 903
 
< 0.1%
0.99 303
 
< 0.1%
0.98 35033
 
0.3%
0.97 538312
4.9%
0.96 156648
 
1.4%
0.95 361836
3.3%
0.94 678932
6.1%
0.93 298199
2.7%
0.92 248311
 
2.2%
0.91 299376
2.7%

esp32_temperature
Real number (ℝ)

ZEROS 

Distinct87
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.100912
Minimum0
Maximum53.3333
Zeros3061149
Zeros (%)27.7%
Negative0
Negative (%)0.0%
Memory size168.8 MiB
2023-07-25T04:30:02.016272image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median31.67
Q333.89
95-th percentile53.3333
Maximum53.3333
Range53.3333
Interquartile range (IQR)33.89

Descriptive statistics

Standard deviation15.987543
Coefficient of variation (CV)0.66335841
Kurtosis-0.83834116
Mean24.100912
Median Absolute Deviation (MAD)4.45
Skewness-0.47949705
Sum2.6669151 × 108
Variance255.60153
MonotonicityNot monotonic
2023-07-25T04:30:02.065468image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3061149
27.7%
33.89 1957975
17.7%
33.33 1318189
11.9%
34.44 669242
 
6.0%
53.3333 660831
 
6.0%
26.67 580106
 
5.2%
27.22 517443
 
4.7%
32.78 413152
 
3.7%
26.11 358328
 
3.2%
32.22 335751
 
3.0%
Other values (77) 1193453
 
10.8%
ValueCountFrequency (%)
0 3061149
27.7%
20.5556 1
 
< 0.1%
20.56 1
 
< 0.1%
21.1111 1
 
< 0.1%
21.6667 2
 
< 0.1%
21.67 13
 
< 0.1%
22.22 774
 
< 0.1%
22.2222 3
 
< 0.1%
22.78 23626
 
0.2%
23.33 21378
 
0.2%
ValueCountFrequency (%)
53.3333 660831
6.0%
52.7778 51
 
< 0.1%
52.2222 74
 
< 0.1%
51.6667 56
 
< 0.1%
51.1111 55
 
< 0.1%
50.5556 64
 
< 0.1%
50 61
 
< 0.1%
49.4444 42
 
< 0.1%
48.8889 61
 
< 0.1%
48.3333 51
 
< 0.1%

workstation_cpu
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct2696
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9972231
Minimum0
Maximum100
Zeros6764177
Zeros (%)61.1%
Negative0
Negative (%)0.0%
Memory size168.8 MiB
2023-07-25T04:30:02.116349image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34.43
95-th percentile8.85
Maximum100
Range100
Interquartile range (IQR)4.43

Descriptive statistics

Standard deviation3.3134864
Coefficient of variation (CV)1.6590467
Kurtosis8.2015163
Mean1.9972231
Median Absolute Deviation (MAD)0
Skewness2.0132835
Sum22100510
Variance10.979192
MonotonicityNot monotonic
2023-07-25T04:30:02.166489image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6764177
61.1%
0.1 187572
 
1.7%
0.2 177318
 
1.6%
0.3 145380
 
1.3%
4.43 129114
 
1.2%
4.3 101019
 
0.9%
0.4 98748
 
0.9%
4.56 90528
 
0.8%
4.36 88841
 
0.8%
4.49 82023
 
0.7%
Other values (2686) 3200899
28.9%
ValueCountFrequency (%)
0 6764177
61.1%
0.1 187572
 
1.7%
0.2 177318
 
1.6%
0.26 1
 
< 0.1%
0.3 145380
 
1.3%
0.4 98748
 
0.9%
0.5 52733
 
0.5%
0.6 29489
 
0.3%
0.7 11675
 
0.1%
0.8 8304
 
0.1%
ValueCountFrequency (%)
100 6
< 0.1%
99.8 5
< 0.1%
99.62 1
 
< 0.1%
99.09 1
 
< 0.1%
98.6 4
< 0.1%
97.53 1
 
< 0.1%
96.74 1
 
< 0.1%
96.61 1
 
< 0.1%
96.22 2
 
< 0.1%
95.44 1
 
< 0.1%

workstation_cpu_power
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1225
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.360714
Minimum0
Maximum46.29
Zeros7758484
Zeros (%)70.1%
Negative0
Negative (%)0.0%
Memory size168.8 MiB
2023-07-25T04:30:02.213339image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q336.97
95-th percentile40.43
Maximum46.29
Range46.29
Interquartile range (IQR)36.97

Descriptive statistics

Standard deviation17.427578
Coefficient of variation (CV)1.5340214
Kurtosis-1.1953699
Mean11.360714
Median Absolute Deviation (MAD)0
Skewness0.88883636
Sum1.2571334 × 108
Variance303.72049
MonotonicityNot monotonic
2023-07-25T04:30:02.258300image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 7758484
70.1%
37.67 78647
 
0.7%
37.58 71798
 
0.6%
37.68 49000
 
0.4%
37.36 47579
 
0.4%
38.25 41225
 
0.4%
37.66 40317
 
0.4%
37.61 40279
 
0.4%
37.77 36555
 
0.3%
37.72 36175
 
0.3%
Other values (1215) 2865560
 
25.9%
ValueCountFrequency (%)
0 7758484
70.1%
33.32 313
 
< 0.1%
33.33 545
 
< 0.1%
33.34 358
 
< 0.1%
33.35 317
 
< 0.1%
33.36 252
 
< 0.1%
33.37 211
 
< 0.1%
33.38 179
 
< 0.1%
33.39 198
 
< 0.1%
33.4 198
 
< 0.1%
ValueCountFrequency (%)
46.29 4
< 0.1%
46.07 6
< 0.1%
45.97 4
< 0.1%
45.94 4
< 0.1%
45.93 1
 
< 0.1%
45.91 4
< 0.1%
45.9 4
< 0.1%
45.88 3
< 0.1%
45.87 7
< 0.1%
45.85 4
< 0.1%

workstation_cpu_temperature
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct68
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.6656744
Minimum0
Maximum165
Zeros7758486
Zeros (%)70.1%
Negative0
Negative (%)0.0%
Memory size168.8 MiB
2023-07-25T04:30:02.307648image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q326
95-th percentile33
Maximum165
Range165
Interquartile range (IQR)26

Descriptive statistics

Standard deviation13.483595
Coefficient of variation (CV)1.5559776
Kurtosis-0.78430312
Mean8.6656744
Median Absolute Deviation (MAD)0
Skewness0.99625473
Sum95891051
Variance181.80734
MonotonicityNot monotonic
2023-07-25T04:30:02.353028image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 7758486
70.1%
27 751880
 
6.8%
26 640354
 
5.8%
28 407809
 
3.7%
25 268911
 
2.4%
29 236227
 
2.1%
30 158598
 
1.4%
31 119613
 
1.1%
32 87037
 
0.8%
36 84514
 
0.8%
Other values (58) 552190
 
5.0%
ValueCountFrequency (%)
0 7758486
70.1%
18 2
 
< 0.1%
21 65
 
< 0.1%
22 176
 
< 0.1%
23 14306
 
0.1%
24 61615
 
0.6%
25 268911
 
2.4%
26 640354
 
5.8%
27 751880
 
6.8%
28 407809
 
3.7%
ValueCountFrequency (%)
165 1
 
< 0.1%
98 1
 
< 0.1%
88 1
 
< 0.1%
84 1
 
< 0.1%
83 2
 
< 0.1%
82 7
< 0.1%
81 2
 
< 0.1%
80 1
 
< 0.1%
79 1
 
< 0.1%
78 11
< 0.1%

workstation_gpu
Real number (ℝ)

ZEROS 

Distinct52
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.035774151
Minimum0
Maximum63
Zeros10793423
Zeros (%)97.5%
Negative0
Negative (%)0.0%
Memory size168.8 MiB
2023-07-25T04:30:02.400569image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum63
Range63
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.31441047
Coefficient of variation (CV)8.7887611
Kurtosis928.91307
Mean0.035774151
Median Absolute Deviation (MAD)0
Skewness19.8574
Sum395863.13
Variance0.098853944
MonotonicityNot monotonic
2023-07-25T04:30:02.449933image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 10793423
97.5%
1 179570
 
1.6%
2 33668
 
0.3%
3 18130
 
0.2%
0.01 17904
 
0.2%
4 7229
 
0.1%
5 4581
 
< 0.1%
0.02 2359
 
< 0.1%
6 2194
 
< 0.1%
0.03 1987
 
< 0.1%
Other values (42) 4574
 
< 0.1%
ValueCountFrequency (%)
0 10793423
97.5%
0.01 17904
 
0.2%
0.02 2359
 
< 0.1%
0.03 1987
 
< 0.1%
0.04 666
 
< 0.1%
0.05 285
 
< 0.1%
0.06 142
 
< 0.1%
0.07 149
 
< 0.1%
0.08 81
 
< 0.1%
0.09 48
 
< 0.1%
ValueCountFrequency (%)
63 1
 
< 0.1%
57 1
 
< 0.1%
40 2
 
< 0.1%
34 1
 
< 0.1%
30 4
< 0.1%
29 3
 
< 0.1%
28 7
< 0.1%
26 7
< 0.1%
25 8
< 0.1%
24 3
 
< 0.1%

workstation_gpu_power
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.115553
Minimum0
Maximum43
Zeros7758486
Zeros (%)70.1%
Negative0
Negative (%)0.0%
Memory size168.8 MiB
2023-07-25T04:30:02.494253image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q333
95-th percentile35
Maximum43
Range43
Interquartile range (IQR)33

Descriptive statistics

Standard deviation15.517828
Coefficient of variation (CV)1.5340563
Kurtosis-1.1976624
Mean10.115553
Median Absolute Deviation (MAD)0
Skewness0.88851294
Sum1.1193485 × 108
Variance240.80299
MonotonicityNot monotonic
2023-07-25T04:30:02.529728image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 7758486
70.1%
34 1210054
 
10.9%
35 836395
 
7.6%
33 523682
 
4.7%
36 293044
 
2.6%
32 185113
 
1.7%
31 81382
 
0.7%
30 75011
 
0.7%
29 60348
 
0.5%
27 27058
 
0.2%
Other values (8) 15046
 
0.1%
ValueCountFrequency (%)
0 7758486
70.1%
27 27058
 
0.2%
28 5810
 
0.1%
29 60348
 
0.5%
30 75011
 
0.7%
31 81382
 
0.7%
32 185113
 
1.7%
33 523682
 
4.7%
34 1210054
 
10.9%
35 836395
 
7.6%
ValueCountFrequency (%)
43 14
 
< 0.1%
42 226
 
< 0.1%
41 698
 
< 0.1%
40 478
 
< 0.1%
39 227
 
< 0.1%
38 351
 
< 0.1%
37 7242
 
0.1%
36 293044
 
2.6%
35 836395
7.6%
34 1210054
10.9%

workstation_gpu_temperature
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct337
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.8942826
Minimum0
Maximum51.04
Zeros8065750
Zeros (%)72.9%
Negative0
Negative (%)0.0%
Memory size168.8 MiB
2023-07-25T04:30:02.821763image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q314.13
95-th percentile14.51
Maximum51.04
Range51.04
Interquartile range (IQR)14.13

Descriptive statistics

Standard deviation6.3977863
Coefficient of variation (CV)1.6428665
Kurtosis-0.66022634
Mean3.8942826
Median Absolute Deviation (MAD)0
Skewness1.0621819
Sum43092648
Variance40.931669
MonotonicityNot monotonic
2023-07-25T04:30:02.868250image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 8065750
72.9%
14.32 569430
 
5.1%
14.42 486260
 
4.4%
14.22 337750
 
3.1%
14.33 281392
 
2.5%
14.23 241006
 
2.2%
14.13 179944
 
1.6%
14.52 156379
 
1.4%
14.51 134180
 
1.2%
14.43 126337
 
1.1%
Other values (327) 487191
 
4.4%
ValueCountFrequency (%)
0 8065750
72.9%
13.08 1
 
< 0.1%
13.18 1
 
< 0.1%
13.27 31
 
< 0.1%
13.28 17
 
< 0.1%
13.35 1
 
< 0.1%
13.36 26
 
< 0.1%
13.37 216
 
< 0.1%
13.45 37
 
< 0.1%
13.46 110
 
< 0.1%
ValueCountFrequency (%)
51.04 1
 
< 0.1%
50.66 1
 
< 0.1%
50.57 1
 
< 0.1%
50.48 1
 
< 0.1%
50.38 1
 
< 0.1%
50.37 2
< 0.1%
50.29 2
< 0.1%
50.22 1
 
< 0.1%
50.21 3
< 0.1%
50.11 2
< 0.1%

workstation_ram
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct3560
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.779082
Minimum0
Maximum55.2
Zeros6675954
Zeros (%)60.3%
Negative0
Negative (%)0.0%
Memory size168.8 MiB
2023-07-25T04:30:02.914305image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q337.21
95-th percentile44.11
Maximum55.2
Range55.2
Interquartile range (IQR)37.21

Descriptive statistics

Standard deviation18.691217
Coefficient of variation (CV)1.2647075
Kurtosis-1.5639621
Mean14.779082
Median Absolute Deviation (MAD)0
Skewness0.55196455
Sum1.635397 × 108
Variance349.36159
MonotonicityNot monotonic
2023-07-25T04:30:02.957997image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6675954
60.3%
42.5 25973
 
0.2%
42.7 22949
 
0.2%
47.5 21099
 
0.2%
44.3 20924
 
0.2%
47.4 20756
 
0.2%
38.95 20305
 
0.2%
38.96 20194
 
0.2%
45.9 20136
 
0.2%
42.3 20102
 
0.2%
Other values (3550) 4197227
37.9%
ValueCountFrequency (%)
0 6675954
60.3%
11.37 1
 
< 0.1%
11.38 40
 
< 0.1%
11.39 29
 
< 0.1%
11.4 161
 
< 0.1%
11.41 62
 
< 0.1%
11.42 15
 
< 0.1%
11.43 56
 
< 0.1%
11.44 21
 
< 0.1%
11.45 45
 
< 0.1%
ValueCountFrequency (%)
55.2 4
 
< 0.1%
55.1 10
< 0.1%
55 17
< 0.1%
54.9 21
< 0.1%
54.8 4
 
< 0.1%
54.7 10
< 0.1%
54.6 8
 
< 0.1%
54.5 13
< 0.1%
54.3 12
< 0.1%
54.2 14
< 0.1%

workstation_ram_power
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1696
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4286255
Minimum0
Maximum46.41
Zeros7758486
Zeros (%)70.1%
Negative0
Negative (%)0.0%
Memory size168.8 MiB
2023-07-25T04:30:03.001992image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q35.44
95-th percentile10.59
Maximum46.41
Range46.41
Interquartile range (IQR)5.44

Descriptive statistics

Standard deviation4.0146946
Coefficient of variation (CV)1.6530727
Kurtosis0.58053689
Mean2.4286255
Median Absolute Deviation (MAD)0
Skewness1.3643011
Sum26874244
Variance16.117773
MonotonicityNot monotonic
2023-07-25T04:30:03.045245image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 7758486
70.1%
7.93 5832
 
0.1%
7.94 5823
 
0.1%
8.07 5815
 
0.1%
8.14 5801
 
0.1%
8.12 5800
 
0.1%
7.96 5793
 
0.1%
8.09 5779
 
0.1%
8.15 5777
 
0.1%
8.25 5772
 
0.1%
Other values (1686) 3254941
29.4%
ValueCountFrequency (%)
0 7758486
70.1%
2.1 1
 
< 0.1%
2.13 1
 
< 0.1%
2.14 1
 
< 0.1%
2.18 3
 
< 0.1%
2.21 1
 
< 0.1%
2.24 1
 
< 0.1%
2.25 1
 
< 0.1%
2.27 3
 
< 0.1%
2.28 3
 
< 0.1%
ValueCountFrequency (%)
46.41 1
 
< 0.1%
34.75 1
 
< 0.1%
27.65 1
 
< 0.1%
24.87 1
 
< 0.1%
22.48 1
 
< 0.1%
22.11 2
 
< 0.1%
21.94 5
< 0.1%
21.78 1
 
< 0.1%
21.63 1
 
< 0.1%
21.59 1
 
< 0.1%

Interactions

2023-07-25T04:29:12.087788image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:15.403567image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:26.531020image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:38.667269image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:50.112910image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:01.335613image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:12.917365image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:23.868111image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:35.169569image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:47.473202image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:00.060914image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:13.324496image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:25.563789image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:37.776311image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:48.993150image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:00.824985image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:12.794168image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:16.134441image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:27.128318image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:39.293845image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:50.751041image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:02.036602image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:13.585396image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:24.493355image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:35.942154image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:48.099871image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:01.170221image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:14.259237image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:26.428623image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:38.535992image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:49.707173image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:01.539868image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:13.562421image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:16.822573image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:27.943917image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:39.877955image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:51.384514image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:02.741654image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:14.267437image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:25.236530image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:36.675798image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:48.792095image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:01.927715image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:15.023146image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:27.285027image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:39.272408image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:50.448854image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:02.309376image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:14.344704image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:17.508528image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:28.798766image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:40.599816image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:51.962690image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:03.451333image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:14.937049image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:25.884495image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:37.498269image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:49.486567image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:02.673439image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:15.801998image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:28.066305image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:40.003116image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:51.224532image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:03.095242image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:15.103521image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:18.242221image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:29.633328image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:41.370886image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:52.660341image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:04.068479image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:15.601594image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:26.564421image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:38.261223image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:50.150868image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:03.393855image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:16.573120image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:28.771466image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:40.699196image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:51.975240image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:03.800455image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:15.865329image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:18.981634image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:30.483662image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:42.115122image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:53.348939image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:04.786030image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:16.177061image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:27.229077image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:39.037201image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:50.830556image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:04.394363image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:17.601556image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:29.524784image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:41.395117image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:52.691569image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:04.533146image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:16.587013image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:19.683455image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:31.176908image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:42.942555image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:54.041906image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:05.481418image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:16.852655image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:27.824869image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:39.750734image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:51.514383image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:05.377497image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:18.445443image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:30.294716image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:42.172091image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:53.491848image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:05.251160image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:17.322884image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:20.381100image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:31.861558image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:43.617665image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:54.720023image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:06.190985image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:17.534354image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:28.645978image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:40.414104image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:52.191191image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:06.227027image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:19.162325image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:31.183157image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:42.930106image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:54.394124image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:05.970853image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:18.072153image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:21.037692image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:32.527641image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:44.318190image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:55.395767image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:06.887309image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:18.196659image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:29.291860image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:41.159789image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:52.750239image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:07.055084image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:19.857690image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:31.973014image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:43.590707image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:55.259328image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:06.686094image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:18.798612image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:21.705318image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:33.214078image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:45.015980image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:56.100073image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:07.589188image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:18.864253image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:30.101876image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:42.144835image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:53.436748image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:07.682673image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:20.543297image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:32.728091image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:44.266070image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:55.977191image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:07.430897image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:19.498156image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:22.450484image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:33.918114image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:45.703580image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:56.837113image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:08.325350image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:19.559076image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:30.845403image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:42.982511image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:54.203225image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:08.368385image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:21.138438image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:33.409826image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:45.002212image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:56.670160image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:08.106746image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:20.410706image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:23.126764image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:35.107250image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:46.407979image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:57.542821image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:09.095897image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:20.260750image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:31.548343image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:43.802412image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:55.421741image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:09.116635image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:21.807736image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:33.987604image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:45.681591image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:57.389198image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:08.797534image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:21.246288image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:23.854542image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:35.817739image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:47.099406image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:58.289681image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:09.902493image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:20.949995image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:32.234133image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:44.498589image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:56.804743image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:09.920857image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:22.625410image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:34.679265image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:46.291019image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:58.087956image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:09.518810image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:21.974588image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:24.484791image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:36.483967image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:47.822785image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:58.979431image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:10.699397image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:21.674421image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:32.974612image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:45.234014image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:57.687249image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:10.606579image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:23.383855image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:35.378643image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:46.965772image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:58.679411image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:10.142042image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:22.665332image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:25.172729image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:37.218234image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:48.552650image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:59.732930image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:11.443905image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:22.412874image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:33.702634image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:46.022010image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:58.450582image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:11.438249image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:24.133977image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:36.142086image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:47.628536image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:59.359280image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:10.710688image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:23.261399image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:25.859483image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:37.951158image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:26:49.343599image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:00.591543image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:12.220434image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:23.143396image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:34.442522image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:46.746583image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:27:59.222912image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:12.400602image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:24.838031image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:36.944262image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:28:48.313871image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:00.104665image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-07-25T04:29:11.392559image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2023-07-25T04:30:03.115367image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
weekdayvoltagecurrentpowerfrequencyenergypower_factoresp32_temperatureworkstation_cpuworkstation_cpu_powerworkstation_cpu_temperatureworkstation_gpuworkstation_gpu_powerworkstation_gpu_temperatureworkstation_ramworkstation_ram_power
weekday1.0000.048-0.045-0.043-0.001-0.0240.0250.115-0.007-0.017-0.016-0.0050.009-0.027-0.031-0.013
voltage0.0481.000-0.821-0.8420.1210.008-0.1880.152-0.606-0.549-0.547-0.133-0.557-0.458-0.567-0.557
current-0.045-0.8211.0000.962-0.006-0.045-0.028-0.2980.5720.4760.4800.0920.4910.4530.5980.473
power-0.043-0.8420.9621.000-0.0030.0080.110-0.2260.6250.5400.5450.1280.5490.5160.6160.537
frequency-0.0010.121-0.006-0.0031.0000.0180.0080.0140.0060.0020.0010.0050.0010.0080.011-0.002
energy-0.0240.008-0.0450.0080.0181.0000.4640.3940.4410.5400.5300.0900.5450.6070.4490.491
power_factor0.025-0.188-0.0280.1100.0080.4641.0000.3720.4360.5090.5210.1360.4960.4570.2620.529
esp32_temperature0.1150.152-0.298-0.2260.0140.3940.3721.0000.2270.1340.1010.1590.1340.0120.2200.109
workstation_cpu-0.007-0.6060.5720.6250.0060.4410.4360.2271.0000.8970.9020.2640.8870.8330.8860.892
workstation_cpu_power-0.017-0.5490.4760.5400.0020.5400.5090.1340.8971.0000.9820.2770.9830.9380.7260.966
workstation_cpu_temperature-0.016-0.5470.4800.5450.0010.5300.5210.1010.9020.9821.0000.2450.9710.9370.7130.989
workstation_gpu-0.005-0.1330.0920.1280.0050.0900.1360.1590.2640.2770.2451.0000.2590.2410.1900.214
workstation_gpu_power0.009-0.5570.4910.5490.0010.5450.4960.1340.8870.9830.9710.2591.0000.9330.7240.960
workstation_gpu_temperature-0.027-0.4580.4530.5160.0080.6070.4570.0120.8330.9380.9370.2410.9331.0000.6980.902
workstation_ram-0.031-0.5670.5980.6160.0110.4490.2620.2200.8860.7260.7130.1900.7240.6981.0000.699
workstation_ram_power-0.013-0.5570.4730.537-0.0020.4910.5290.1090.8920.9660.9890.2140.9600.9020.6991.000

Missing values

2023-07-25T04:29:23.715835image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2023-07-25T04:29:33.065138image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

weekdayvoltagecurrentpowerfrequencyenergypower_factoresp32_temperatureworkstation_cpuworkstation_cpu_powerworkstation_cpu_temperatureworkstation_gpuworkstation_gpu_powerworkstation_gpu_temperatureworkstation_ramworkstation_ram_power
fecha_servidor
2021-05-05 22:05:273119.91.15126.460.00.00.920.00.00.000.000.00.00.0
2021-05-05 22:05:283119.91.15126.460.00.00.920.00.00.000.000.00.00.0
2021-05-05 22:05:283119.91.09118.560.00.00.910.00.00.000.000.00.00.0
2021-05-05 22:05:293119.91.09118.560.00.00.910.00.00.000.000.00.00.0
2021-05-05 22:05:293120.01.01107.760.00.00.890.00.00.000.000.00.00.0
2021-05-05 22:05:303120.01.01107.760.00.00.890.00.00.000.000.00.00.0
2021-05-05 22:05:303120.00.96100.960.00.00.870.00.00.000.000.00.00.0
2021-05-05 22:05:313120.00.96100.960.00.00.870.00.00.000.000.00.00.0
2021-05-05 22:05:323120.01.00105.460.00.00.880.00.00.000.000.00.00.0
2021-05-05 22:05:333120.00.97101.660.00.00.880.00.00.000.000.00.00.0
weekdayvoltagecurrentpowerfrequencyenergypower_factoresp32_temperatureworkstation_cpuworkstation_cpu_powerworkstation_cpu_temperatureworkstation_gpuworkstation_gpu_powerworkstation_gpu_temperatureworkstation_ramworkstation_ram_power
fecha_servidor
2021-12-04 08:18:086118.80.70180.359.924.8500.9653.33335.2134.68250.0300.0024.958.69
2021-12-04 08:18:086119.61.047111.959.9442.6260.8953.333313.6938.38340.03414.1348.565.36
2021-12-04 08:18:086119.61.031110.559.9442.6260.9053.33337.5438.38260.03414.3348.553.89
2021-12-04 08:18:096118.80.70781.459.924.8500.9753.33335.2634.68250.0300.0024.958.36
2021-12-04 08:18:096119.61.152125.460.0442.6260.9153.33335.7738.38250.03414.3348.553.63
2021-12-04 08:18:106118.80.71282.359.924.8500.9753.33335.0834.68260.0300.0024.958.31
2021-12-04 08:18:116118.90.67578.559.924.8500.9853.33335.2134.68260.0300.0024.948.31
2021-12-04 08:18:116119.61.189130.359.9442.6260.9253.333313.1838.38350.03414.2348.585.58
2021-12-04 08:18:116119.61.152125.459.9442.6260.9153.333313.1838.38350.03414.2348.585.58
2021-12-04 08:18:126118.80.69180.059.924.8500.9753.33334.4334.68250.0300.0024.957.71

Duplicate rows

Most frequently occurring

weekdayvoltagecurrentpowerfrequencyenergypower_factoresp32_temperatureworkstation_cpuworkstation_cpu_powerworkstation_cpu_temperatureworkstation_gpuworkstation_gpu_powerworkstation_gpu_temperatureworkstation_ramworkstation_ram_power# duplicates
8953186120.50.134.960.0136.650.3234.440.00.000.000.00.00.03417
10656617120.50.134.960.0136.770.3234.440.00.000.000.00.00.03154
10656567120.50.134.960.0136.760.3234.440.00.000.000.00.00.03138
8953066120.50.134.960.0136.630.3234.440.00.000.000.00.00.03107
8952996120.50.134.960.0136.620.3234.440.00.000.000.00.00.03077
3011822120.50.134.960.0137.020.3234.440.00.000.000.00.00.03028
8953236120.50.134.960.0136.660.3234.440.00.000.000.00.00.02991
8953136120.50.134.960.0136.640.3234.440.00.000.000.00.00.02725
5595034120.50.134.960.0136.400.3233.890.00.000.000.00.00.02704
10656467120.50.134.960.0136.740.3234.440.00.000.000.00.00.02701